Identifying the modular structures in protein interaction networks

  • Authors:

  • Yanen Li;Feng Lu;Yanhong Zhou

  • Affiliations:

  • Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan, Hubei, China;Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan, Hubei, China;Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan, Hubei, China

  • Venue:
  • ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
  • Year:
  • 2006

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Abstract

Identifying the modular structures in Protein Interaction Networks (PINs) is crucial to the understanding of the organization and function of biological systems. We propose a new module definition taking into account the degree of a subgraph instead of a vertice, and design a corresponding agglomerative algorithm, which is implemented into a computational tool called ModuleSpider, to recognize modules within a network. The application of ModuleSpider to the yeast core protein interaction network identifies 97 simple modules which are biologically meaningful according to the GO annotation of proteins in the modules. In addition, the results of comparison analysis demonstrate that ModuleSpider modules show stronger biological relevance. Further, the ModuleSpider is able to construct the interaction web of modules, which provides insights to the high level relationships of different functional modules. ModuleSpider is freely available upon request to the authors.